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2017 Projects: Drones for Yield Predictions and N Management Decisions

How Best to Use of Unmanned Aerial Systems (UAS) for Management of Corn and Sorghum?

Precision agriculture is moving toward the implementation of technology-driven farm management packages that also help with making better decisions about crop fertility management (decision agriculture). Of all nutrients essential for crop growth, N is most difficult to manage due to varying crop N demands throughout the season and inability to accurately predict N supply. Use of drone-obtained NDVI images has the promise to aid in quick and accurate decision making for better N management of field crops like corn and forage sorghum that have large and well-timed N needs but requires accurate estimation of (1) end-of-season yield; (2) soil N supply; and (3) crop N needs. Our overall objective here is to evaluate use of drone-collected images as tools for predicting yield and N needs for both crops.

If you are interested in participating, contact Quirine Ketterings (qmk2@cornell.edu or 607-255-3061). You can also write to: Quirine Ketterings, Nutrient Management Spear Program, Department of Animal Science, Cornell University, 323 Morrison Hall, Ithaca NY 14853.

Goals

    Our goals are to evaluate use of drone collected images for yield predictions of N responsiveness and needs for corn and forage sorghum as impacted by timing of flight (in the day and over the growing season).

Funding Sources

New York Farm Viability Institute, Federal Formula Funds, DuPont-Pioneer

Additional Resources

Farmer Impact Stories

Fact Sheets

Extension Articles

Journal Articles